中文
相关论文

相关论文: Large Language Models for Time Series: A Survey

200 篇论文

Large language models (LLMs) have revolutionized video-based computer vision applications, including action recognition, anomaly detection, and video summarization. Videos inherently pose unique challenges, combining spatial complexity with…

计算机视觉与模式识别 · 计算机科学 2025-02-25 Xi Ding , Lei Wang

Time series forecasting is critical across multiple domains, where time series data exhibit both local patterns and global dependencies. While Transformer-based methods effectively capture global dependencies, they often overlook short-term…

机器学习 · 计算机科学 2026-04-17 Wenjie Ou , Zhishuo Zhao , Cheng Chen , Dongyue Guo , Yi Lin

Large language models (LLMs) and transformer-based architectures are increasingly utilized for source code analysis. As software systems grow in complexity, integrating LLMs into code analysis workflows becomes essential for enhancing…

软件工程 · 计算机科学 2025-03-25 Hamed Jelodar , Mohammad Meymani , Roozbeh Razavi-Far

Machine learning can provide deep insights into data, allowing machines to make high-quality predictions and having been widely used in real-world applications, such as text mining, visual classification, and recommender systems. However,…

机器学习 · 计算机科学 2020-08-11 Meng Wang , Weijie Fu , Xiangnan He , Shijie Hao , Xindong Wu

Objective: Large language models (LLMs) are attracting increasing interest in healthcare. This commentary evaluates the potential of LLMs to improve clinical prediction models (CPMs) for diagnostic and prognostic tasks, with a focus on…

计算机与社会 · 计算机科学 2025-11-07 Yusuf Yildiz , Goran Nenadic , Meghna Jani , David A. Jenkins

Large Language Models (LLMs) have transformed numerous domains by providing advanced capabilities in natural language understanding, generation, and reasoning. Despite their groundbreaking applications across industries such as research,…

人工智能 · 计算机科学 2025-01-22 Aditi Singh , Nirmal Prakashbhai Patel , Abul Ehtesham , Saket Kumar , Tala Talaei Khoei

The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a…

Large language models (LLMs) have revolutionized natural language processing with their exceptional understanding, synthesizing, and reasoning capabilities. However, deploying LLMs on resource-constrained edge devices presents significant…

分布式、并行与集群计算 · 计算机科学 2025-02-25 Yue Zheng , Yuhao Chen , Bin Qian , Xiufang Shi , Yuanchao Shu , Jiming Chen

Large Language Models (LLMs) have seen rapid advancements in recent years, with models like ChatGPT and DeepSeek, showcasing their remarkable capabilities across diverse domains. While substantial research has been conducted on LLMs in…

机器学习 · 计算机科学 2026-03-31 Licheng Zhang , Bach Le , Naveed Akhtar , Siew-Kei Lam , Tuan Ngo

The use of Large Language Models (LLMs) has drawn growing interest within the scientific community. LLMs can handle large volumes of textual data and support methods for evidence synthesis. Although recent studies highlight the potential of…

The rapid evolution of communication networks in recent decades has intensified the need for advanced Network and Service Management (NSM) strategies to address the growing demands for efficiency, scalability, enhanced performance, and…

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

A Large Language Model (LLM) represents a cutting-edge artificial intelligence model that generates coherent content, including grammatically precise sentences, human-like paragraphs, and syntactically accurate code snippets. LLMs can play…

软件工程 · 计算机科学 2023-12-11 Robson Santos , Italo Santos , Cleyton Magalhaes , Ronnie de Souza Santos

In the wake of relentless digital transformation, data-driven solutions are emerging as powerful tools to address multifarious industrial tasks such as forecasting, anomaly detection, planning, and even complex decision-making. Although…

人工智能 · 计算机科学 2023-10-18 Xu Yang , Xiao Yang , Weiqing Liu , Jinhui Li , Peng Yu , Zeqi Ye , Jiang Bian

Mobility analysis is a crucial element in the research area of transportation systems. Forecasting traffic information offers a viable solution to address the conflict between increasing transportation demands and the limitations of…

机器学习 · 计算机科学 2025-02-24 Zijian Zhang , Yujie Sun , Zepu Wang , Yuqi Nie , Xiaobo Ma , Ruolin Li , Peng Sun , Xuegang Ban

The advent of Large Language Models (LLMs) has significantly reshaped the trajectory of the AI revolution. Nevertheless, these LLMs exhibit a notable limitation, as they are primarily adept at processing textual information. To address this…

计算机视觉与模式识别 · 计算机科学 2025-10-15 Akash Ghosh , Arkadeep Acharya , Sriparna Saha , Vinija Jain , Aman Chadha

Building effective machine learning (ML) workflows to address complex tasks is a primary focus of the Automatic ML (AutoML) community and a critical step toward achieving artificial general intelligence (AGI). Recently, the integration of…

机器学习 · 计算机科学 2024-12-30 Yang Gu , Hengyu You , Jian Cao , Muran Yu , Haoran Fan , Shiyou Qian

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

人工智能 · 计算机科学 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

Recent work exploring the capabilities of pre-trained large language models (LLMs) has demonstrated their ability to act as general pattern machines by completing complex token sequences representing a wide array of tasks, including…

计算机与社会 · 计算机科学 2024-03-25 Seyed Parsa Neshaei , Richard Lee Davis , Adam Hazimeh , Bojan Lazarevski , Pierre Dillenbourg , Tanja Käser

This paper provides a primer on Large Language Models (LLMs) and identifies their strengths, limitations, applications and research directions. It is intended to be useful to those in academia and industry who are interested in gaining an…

计算与语言 · 计算机科学 2024-12-09 Sandra Johnson , David Hyland-Wood